RESUMO
Understanding trophic interactions in agroecosystems is crucial for harnessing ecosystem services such as pest control, thus enabling a reduction in pesticide use. Carabid beetles (Coleoptera: Carabidae) have the potential to regulate not only insect pests but also weed seeds and slugs. The aim of this study was to investigate the food choice of different carabid species in the experimental setting of a cereal field with varying seed and slug prey availability during the season. In addition to varying food availability, the effects of species identity and season on carabid food choice should also be closely examined. Therefore, the gut contents of 1,120 beetles of eight carabid species were screened for the DNA of plants, aphids, springtails, earthworms and slugs via diagnostic multiplex PCR and a nested metabarcoding approach for plant species identification. Plant DNA was detected far more often (72%) than the various animal prey types (less than 12.5% each). Within the plant detections, 80 weed species were identified in the metabarcoding, with Galinsoga parviflora/quadriradiata (Galinsoga spp.-quickweeds) as the most frequently detected species. Carabid food choice was driven by their species identity and seasonality, while no effect of increased availability of seeds and slugs on their food choice was detected. While weed seeds seem to be an important food source for carabids, their availability does not directly affect the carabid diet. The importance of consumer identity and seasonality highlight the need for a diverse carabid species community for resilient pest control services. Supplementary Information: The online version contains supplementary material available at 10.1007/s10340-023-01620-w.
RESUMO
High-throughput sequencing platforms are increasingly being used for targeted amplicon sequencing because they enable cost-effective sequencing of large sample sets. For meaningful interpretation of targeted amplicon sequencing data and comparison between studies, it is critical that bioinformatic analyses do not introduce artefacts and rely on detailed protocols to ensure that all methods are properly performed and documented. The analysis of large sample sets and the use of predefined indexes create challenges, such as adjusting the sequencing depth across samples and taking sequencing errors or index hopping into account. However, the potential biases these factors introduce to high-throughput amplicon sequencing data sets and how they may be overcome have rarely been addressed. On the example of a nested metabarcoding analysis of 1920 carabid beetle regurgitates to assess plant feeding, we investigated: (i) the variation in sequencing depth of individually tagged samples and the effect of library preparation on the data output; (ii) the influence of sequencing errors within index regions and its consequences for demultiplexing; and (iii) the effect of index hopping. Our results demonstrate that despite library quantification, large variation in read counts and sequencing depth occurred among samples and that the sequencing error rate in bioinformatic software is essential for accurate adapter/primer trimming and demultiplexing. Moreover, setting an index hopping threshold to avoid incorrect assignment of samples is highly recommended.
